Between Inclusion and Artificial Intelligence: A Study of the Training Gaps of University Teaching Staff in Spain

Abstract

This study analyzes how Spanish universities integrate inclusion, accessibility, digital competence, and artificial intelligence (AI) into the professional development of university teaching staff, in a context marked by rapid digital transformation. The research addresses the lack of comparative evidence on how these key dimensions of contemporary higher education are articulated, or remain disconnected, across institutions. Using a mixed-methods design, 83 training courses delivered between 2020 and 2025 in 24 public and private universities were examined through qualitative analysis, coding matrices, and hierarchical cluster analysis. The study adopts an explicitly exploratory and typological approach, aimed at mapping institutional patterns rather than establishing causal explanations. The results reveal a highly heterogeneous and weakly cohesive training landscape. Inclusion appears primarily as a normative discourse with limited pedagogical depth; accessibility is frequently reduced to technical compliance; and AI (particularly generative AI) is incorporated from instrumental, efficiency-oriented approaches. Ethical dimensions, algorithmic bias, and digital accessibility are virtually absent. The hierarchical cluster analysis identifies four institutional profiles: technocentric without inclusion, analogically inclusive, advanced hybrid, and low-density training models. These patterns show how institutional orientations shape the professional development trajectories of university teaching staff. The study highlights the need for comprehensive faculty development strategies that integrate inclusion, accessibility, and responsible AI use, and offers a structured typological baseline for future research assessing impact on teaching practice and student experience.